Overview

Brought to you by YData

Dataset statistics

Number of variables	22
Number of observations	74
Missing cells	103
Missing cells (%)	6.3%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	72.1 KiB
Average record size in memory	998.1 B

Variable types

Numeric	7
Text	6
Categorical	9

Alerts

`balls_left` is highly overall correlated with `first_ings_score` and 2 other fields	High correlation
`first_ings_score` is highly overall correlated with `balls_left` and 3 other fields	High correlation
`first_ings_wkts` is highly overall correlated with `first_ings_score`	High correlation
`highscore` is highly overall correlated with `first_ings_score` and 2 other fields	High correlation
`match_result` is highly overall correlated with `balls_left` and 4 other fields	High correlation
`match_winner` is highly overall correlated with `match_result`	High correlation
`second_ings_score` is highly overall correlated with `first_ings_score` and 2 other fields	High correlation
`second_ings_wkts` is highly overall correlated with `balls_left` and 1 other fields	High correlation
`team1` is highly overall correlated with `venue`	High correlation
`team2` is highly overall correlated with `toss_winner`	High correlation
`toss_winner` is highly overall correlated with `team2`	High correlation
`venue` is highly overall correlated with `team1`	High correlation
`wb_wickets` is highly overall correlated with `match_result` and 1 other fields	High correlation
`stage` is highly imbalanced (78.1%)	Imbalance
`match_result` is highly imbalanced (75.5%)	Imbalance
`toss_winner` has 1 (1.4%) missing values	Missing
`first_ings_score` has 1 (1.4%) missing values	Missing
`first_ings_wkts` has 1 (1.4%) missing values	Missing
`second_ings_score` has 2 (2.7%) missing values	Missing
`second_ings_wkts` has 2 (2.7%) missing values	Missing
`match_winner` has 3 (4.1%) missing values	Missing
`wb_runs` has 40 (54.1%) missing values	Missing
`wb_wickets` has 36 (48.6%) missing values	Missing
`balls_left` has 2 (2.7%) missing values	Missing
`player_of_the_match` has 3 (4.1%) missing values	Missing
`top_scorer` has 3 (4.1%) missing values	Missing
`highscore` has 3 (4.1%) missing values	Missing
`best_bowling` has 3 (4.1%) missing values	Missing
`best_bowling_figure` has 3 (4.1%) missing values	Missing
`match_id` is uniformly distributed	Uniform
`team1` is uniformly distributed	Uniform
`team2` is uniformly distributed	Uniform
`match_id` has unique values	Unique
`second_ings_wkts` has 2 (2.7%) zeros	Zeros
`balls_left` has 26 (35.1%) zeros	Zeros

Reproduction

Analysis started	2025-08-13 16:56:07.054775
Analysis finished	2025-08-13 16:56:16.675706
Duration	9.62 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

match_id
Real number (ℝ)

Uniform Unique

Distinct	74
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	37.5

Minimum	1
Maximum	74
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	724.0 B

Quantile statistics

Minimum	1
5-th percentile	4.65
Q1	19.25
median	37.5
Q3	55.75
95-th percentile	70.35
Maximum	74
Range	73
Interquartile range (IQR)	36.5

Descriptive statistics

Standard deviation	21.505813
Coefficient of variation (CV)	0.57348835
Kurtosis	-1.2
Mean	37.5
Median Absolute Deviation (MAD)	18.5
Skewness	0
Sum	2775
Variance	462.5
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	1.4%
2	1	1.4%
3	1	1.4%
4	1	1.4%
5	1	1.4%
6	1	1.4%
7	1	1.4%
8	1	1.4%
9	1	1.4%
10	1	1.4%
Other values (64)	64	86.5%

Value	Count	Frequency (%)
1	1	1.4%
2	1	1.4%
3	1	1.4%
4	1	1.4%
5	1	1.4%
6	1	1.4%
7	1	1.4%
8	1	1.4%
9	1	1.4%
10	1	1.4%

Value	Count	Frequency (%)
74	1	1.4%
73	1	1.4%
72	1	1.4%
71	1	1.4%
70	1	1.4%
69	1	1.4%
68	1	1.4%
67	1	1.4%
66	1	1.4%
65	1	1.4%

date
Text

Distinct	62
Distinct (%)	83.8%
Missing	0
Missing (%)	0.0%
Memory size	5.1 KiB

Length

Max length	13
Median length	13
Mean length	12.216216
Min length	10

Characters and Unicode

Total characters	904
Distinct characters	26
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	50 ?
Unique (%)	67.6%

Sample

1st row	March 22,2025
2nd row	March 23,2025
3rd row	March 23,2025
4th row	March 24,2025
5th row	March 25,2025

Value	Count	Frequency (%)
april	37	25.0%
may	23	15.5%
march	12	8.1%
23,2025	4	2.7%
27,2025	4	2.7%
30,2025	4	2.7%
25,2025	4	2.7%
18,2025	3	2.0%
19,2025	3	2.0%
20,2025	3	2.0%
Other values (32)	51	34.5%

Most occurring characters

Value	Count	Frequency (%)
2	186	20.6%
0	93	10.3%
5	82	9.1%
	74	8.2%
,	74	8.2%
r	49	5.4%
i	37	4.1%
p	37	4.1%
A	37	4.1%
l	37	4.1%
Other values (16)	198	21.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	904	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
2	186	20.6%
0	93	10.3%
5	82	9.1%
	74	8.2%
,	74	8.2%
r	49	5.4%
i	37	4.1%
p	37	4.1%
A	37	4.1%
l	37	4.1%
Other values (16)	198	21.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	904	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
2	186	20.6%
0	93	10.3%
5	82	9.1%
	74	8.2%
,	74	8.2%
r	49	5.4%
i	37	4.1%
p	37	4.1%
A	37	4.1%
l	37	4.1%
Other values (16)	198	21.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	904	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
2	186	20.6%
0	93	10.3%
5	82	9.1%
	74	8.2%
,	74	8.2%
r	49	5.4%
i	37	4.1%
p	37	4.1%
A	37	4.1%
l	37	4.1%
Other values (16)	198	21.9%

venue
Categorical

High correlation

Distinct	13
Distinct (%)	17.6%
Missing	0
Missing (%)	0.0%
Memory size	6.5 KiB

Narendra Modi Stadium, Ahmedabad	9
Ekana Cricket Stadium, Lucknow	8
Eden Gardens, Kolkata	7
Wankhede Stadium, Mumbai	7
Arun Jaitley Stadium, Delhi	7
Other values (8)	36

Length

Max length	45
Median length	33
Mean length	30.527027
Min length	21

Characters and Unicode

Total characters	2259
Distinct characters	44
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.4%

Sample

1st row	Eden Gardens, Kolkata
2nd row	Rajiv Gandhi International Stadium, Hyderabad
3rd row	MA Chidambaram Stadium, Chennai
4th row	ACA-VDCA Cricket Stadium, Vishakhapatnam
5th row	Narendra Modi Stadium, Ahmedabad

Common Values

Value	Count	Frequency (%)
Narendra Modi Stadium, Ahmedabad	9	12.2%
Ekana Cricket Stadium, Lucknow	8	10.8%
Eden Gardens, Kolkata	7	9.5%
Wankhede Stadium, Mumbai	7	9.5%
Arun Jaitley Stadium, Delhi	7	9.5%
Sawai Mansingh Stadium, Jaipur	7	9.5%
New PCA Cricket Stadium, Mullanpur	6	8.1%
Rajiv Gandhi International Stadium, Hyderabad	6	8.1%
MA Chidambaram Stadium, Chennai	6	8.1%
M. Chinnaswamy Stadium, Bangalore	6	8.1%
Other values (3)	5	6.8%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
stadium	67	23.0%
cricket	16	5.5%
narendra	9	3.1%
ahmedabad	9	3.1%
modi	9	3.1%
ekana	8	2.7%
lucknow	8	2.7%
eden	7	2.4%
gardens	7	2.4%
kolkata	7	2.4%
Other values (27)	144	49.5%

Most occurring characters

Value	Count	Frequency (%)
a	303	13.4%
	217	9.6%
i	174	7.7%
d	148	6.6%
n	129	5.7%
t	113	5.0%
u	110	4.9%
e	106	4.7%
m	104	4.6%
r	90	4.0%
Other values (34)	765	33.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	2259	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	303	13.4%
	217	9.6%
i	174	7.7%
d	148	6.6%
n	129	5.7%
t	113	5.0%
u	110	4.9%
e	106	4.7%
m	104	4.6%
r	90	4.0%
Other values (34)	765	33.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	2259	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	303	13.4%
	217	9.6%
i	174	7.7%
d	148	6.6%
n	129	5.7%
t	113	5.0%
u	110	4.9%
e	106	4.7%
m	104	4.6%
r	90	4.0%
Other values (34)	765	33.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	2259	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	303	13.4%
	217	9.6%
i	174	7.7%
d	148	6.6%
n	129	5.7%
t	113	5.0%
u	110	4.9%
e	106	4.7%
m	104	4.6%
r	90	4.0%
Other values (34)	765	33.9%

team1
Categorical

High correlation Uniform

Distinct	10
Distinct (%)	13.5%
Missing	0
Missing (%)	0.0%
Memory size	4.4 KiB

PBKS	9
KKR	8
RCB	8
GT	8
RR	7
Other values (5)	34

Length

Max length	4
Median length	3
Mean length	2.7297297
Min length	2

Characters and Unicode

Total characters	202
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	KKR
2nd row	SRH
3rd row	CSK
4th row	DC
5th row	GT

Common Values

Value	Count	Frequency (%)
PBKS	9	12.2%
KKR	8	10.8%
RCB	8	10.8%
GT	8	10.8%
RR	7	9.5%
CSK	7	9.5%
LSG	7	9.5%
DC	7	9.5%
MI	7	9.5%
SRH	6	8.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
pbks	9	12.2%
kkr	8	10.8%
rcb	8	10.8%
gt	8	10.8%
rr	7	9.5%
csk	7	9.5%
lsg	7	9.5%
dc	7	9.5%
mi	7	9.5%
srh	6	8.1%

Most occurring characters

Value	Count	Frequency (%)
R	36	17.8%
K	32	15.8%
S	29	14.4%
C	22	10.9%
B	17	8.4%
G	15	7.4%
P	9	4.5%
T	8	4.0%
L	7	3.5%
D	7	3.5%
Other values (3)	20	9.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	202	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
R	36	17.8%
K	32	15.8%
S	29	14.4%
C	22	10.9%
B	17	8.4%
G	15	7.4%
P	9	4.5%
T	8	4.0%
L	7	3.5%
D	7	3.5%
Other values (3)	20	9.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	202	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
R	36	17.8%
K	32	15.8%
S	29	14.4%
C	22	10.9%
B	17	8.4%
G	15	7.4%
P	9	4.5%
T	8	4.0%
L	7	3.5%
D	7	3.5%
Other values (3)	20	9.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	202	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
R	36	17.8%
K	32	15.8%
S	29	14.4%
C	22	10.9%
B	17	8.4%
G	15	7.4%
P	9	4.5%
T	8	4.0%
L	7	3.5%
D	7	3.5%
Other values (3)	20	9.9%

team2
Categorical

High correlation Uniform

Distinct	10
Distinct (%)	13.5%
Missing	0
Missing (%)	0.0%
Memory size	4.4 KiB

MI	9
RCB	8
SRH	8
PBKS	8
RR	7
Other values (5)	34

Length

Max length	4
Median length	3
Mean length	2.7027027
Min length	2

Characters and Unicode

Total characters	200
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	RCB
2nd row	RR
3rd row	MI
4th row	LSG
5th row	PBKS

Common Values

Value	Count	Frequency (%)
MI	9	12.2%
RCB	8	10.8%
SRH	8	10.8%
PBKS	8	10.8%
RR	7	9.5%
LSG	7	9.5%
GT	7	9.5%
CSK	7	9.5%
DC	7	9.5%
KKR	6	8.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
mi	9	12.2%
rcb	8	10.8%
srh	8	10.8%
pbks	8	10.8%
rr	7	9.5%
lsg	7	9.5%
gt	7	9.5%
csk	7	9.5%
dc	7	9.5%
kkr	6	8.1%

Most occurring characters

Value	Count	Frequency (%)
R	36	18.0%
S	30	15.0%
K	27	13.5%
C	22	11.0%
B	16	8.0%
G	14	7.0%
M	9	4.5%
I	9	4.5%
H	8	4.0%
P	8	4.0%
Other values (3)	21	10.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	200	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
R	36	18.0%
S	30	15.0%
K	27	13.5%
C	22	11.0%
B	16	8.0%
G	14	7.0%
M	9	4.5%
I	9	4.5%
H	8	4.0%
P	8	4.0%
Other values (3)	21	10.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	200	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
R	36	18.0%
S	30	15.0%
K	27	13.5%
C	22	11.0%
B	16	8.0%
G	14	7.0%
M	9	4.5%
I	9	4.5%
H	8	4.0%
P	8	4.0%
Other values (3)	21	10.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	200	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
R	36	18.0%
S	30	15.0%
K	27	13.5%
C	22	11.0%
B	16	8.0%
G	14	7.0%
M	9	4.5%
I	9	4.5%
H	8	4.0%
P	8	4.0%
Other values (3)	21	10.5%

stage
Categorical

Imbalance

Distinct	3
Distinct (%)	4.1%
Missing	0
Missing (%)	0.0%
Memory size	4.7 KiB

League	70
Playoffs	3
Final	1

Length

Max length	8
Median length	6
Mean length	6.0675676
Min length	5

Characters and Unicode

Total characters	449
Distinct characters	14
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	1.4%

Sample

1st row	League
2nd row	League
3rd row	League
4th row	League
5th row	League

Common Values

Value	Count	Frequency (%)
League	70	94.6%
Playoffs	3	4.1%
Final	1	1.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
league	70	94.6%
playoffs	3	4.1%
final	1	1.4%

Most occurring characters

Value	Count	Frequency (%)
e	140	31.2%
a	74	16.5%
L	70	15.6%
g	70	15.6%
u	70	15.6%
f	6	1.3%
l	4	0.9%
P	3	0.7%
y	3	0.7%
o	3	0.7%
Other values (4)	6	1.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	449	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	140	31.2%
a	74	16.5%
L	70	15.6%
g	70	15.6%
u	70	15.6%
f	6	1.3%
l	4	0.9%
P	3	0.7%
y	3	0.7%
o	3	0.7%
Other values (4)	6	1.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	449	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	140	31.2%
a	74	16.5%
L	70	15.6%
g	70	15.6%
u	70	15.6%
f	6	1.3%
l	4	0.9%
P	3	0.7%
y	3	0.7%
o	3	0.7%
Other values (4)	6	1.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	449	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	140	31.2%
a	74	16.5%
L	70	15.6%
g	70	15.6%
u	70	15.6%
f	6	1.3%
l	4	0.9%
P	3	0.7%
y	3	0.7%
o	3	0.7%
Other values (4)	6	1.3%

toss_winner
Categorical

High correlation Missing

Distinct	10
Distinct (%)	13.7%
Missing	1
Missing (%)	1.4%
Memory size	4.5 KiB

PBKS	12
DC	8
SRH	8
MI	7
RR	7
Other values (5)	31

Length

Max length	4
Median length	3
Mean length	2.7671233
Min length	2

Characters and Unicode

Total characters	202
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	RCB
2nd row	RR
3rd row	CSK
4th row	DC
5th row	GT

Common Values

Value	Count	Frequency (%)
PBKS	12	16.2%
DC	8	10.8%
SRH	8	10.8%
MI	7	9.5%
RR	7	9.5%
RCB	7	9.5%
GT	7	9.5%
CSK	6	8.1%
KKR	6	8.1%
LSG	5	6.8%
(Missing)	1	1.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
pbks	12	16.4%
dc	8	11.0%
srh	8	11.0%
mi	7	9.6%
rr	7	9.6%
rcb	7	9.6%
gt	7	9.6%
csk	6	8.2%
kkr	6	8.2%
lsg	5	6.8%

Most occurring characters

Value	Count	Frequency (%)
R	35	17.3%
S	31	15.3%
K	30	14.9%
C	21	10.4%
B	19	9.4%
G	12	5.9%
P	12	5.9%
D	8	4.0%
H	8	4.0%
M	7	3.5%
Other values (3)	19	9.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	202	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
R	35	17.3%
S	31	15.3%
K	30	14.9%
C	21	10.4%
B	19	9.4%
G	12	5.9%
P	12	5.9%
D	8	4.0%
H	8	4.0%
M	7	3.5%
Other values (3)	19	9.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	202	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
R	35	17.3%
S	31	15.3%
K	30	14.9%
C	21	10.4%
B	19	9.4%
G	12	5.9%
P	12	5.9%
D	8	4.0%
H	8	4.0%
M	7	3.5%
Other values (3)	19	9.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	202	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
R	35	17.3%
S	31	15.3%
K	30	14.9%
C	21	10.4%
B	19	9.4%
G	12	5.9%
P	12	5.9%
D	8	4.0%
H	8	4.0%
M	7	3.5%
Other values (3)	19	9.4%

toss_decision
Categorical

Distinct	2
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Memory size	4.5 KiB

Bowl	61
Bat	13

Length

Max length	4
Median length	4
Mean length	3.8243243
Min length	3

Characters and Unicode

Total characters	283
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Bowl
2nd row	Bowl
3rd row	Bowl
4th row	Bowl
5th row	Bowl

Common Values

Value	Count	Frequency (%)
Bowl	61	82.4%
Bat	13	17.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
bowl	61	82.4%
bat	13	17.6%

Most occurring characters

Value	Count	Frequency (%)
B	74	26.1%
o	61	21.6%
w	61	21.6%
l	61	21.6%
a	13	4.6%
t	13	4.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	283	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
B	74	26.1%
o	61	21.6%
w	61	21.6%
l	61	21.6%
a	13	4.6%
t	13	4.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	283	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
B	74	26.1%
o	61	21.6%
w	61	21.6%
l	61	21.6%
a	13	4.6%
t	13	4.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	283	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
B	74	26.1%
o	61	21.6%
w	61	21.6%
l	61	21.6%
a	13	4.6%
t	13	4.6%

first_ings_score
Real number (ℝ)

High correlation Missing

Distinct	56
Distinct (%)	76.7%
Missing	1
Missing (%)	1.4%
Infinite	0
Infinite (%)	0.0%
Mean	189.75342

Minimum	95
Maximum	286
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	724.0 B

Quantile statistics

Minimum	95
5-th percentile	114
Q1	166
median	196
Q3	213
95-th percentile	240
Maximum	286
Range	191
Interquartile range (IQR)	47

Descriptive statistics

Standard deviation	37.489547
Coefficient of variation (CV)	0.1975698
Kurtosis	0.61883518
Mean	189.75342
Median Absolute Deviation (MAD)	23
Skewness	-0.30442583
Sum	13852
Variance	1405.4661
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
205	4	5.4%
203	3	4.1%
180	3	4.1%
190	3	4.1%
163	2	2.7%
219	2	2.7%
155	2	2.7%
196	2	2.7%
209	2	2.7%
217	2	2.7%
Other values (46)	48	64.9%

Value	Count	Frequency (%)
95	1	1.4%
101	1	1.4%
103	1	1.4%
111	1	1.4%
116	1	1.4%
133	1	1.4%
143	1	1.4%
151	1	1.4%
152	1	1.4%
154	1	1.4%

Value	Count	Frequency (%)
286	1	1.4%
278	1	1.4%
245	1	1.4%
243	1	1.4%
238	1	1.4%
236	1	1.4%
235	1	1.4%
231	1	1.4%
230	1	1.4%
228	1	1.4%

first_ings_wkts
Real number (ℝ)

High correlation Missing

Distinct	9
Distinct (%)	12.3%
Missing	1
Missing (%)	1.4%
Infinite	0
Infinite (%)	0.0%
Mean	6.4520548

Minimum	2
Maximum	10
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	724.0 B

Quantile statistics

Minimum	2
5-th percentile	3
Q1	5
median	6
Q3	8
95-th percentile	10
Maximum	10
Range	8
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	2.1084558
Coefficient of variation (CV)	0.32678827
Kurtosis	-0.76366812
Mean	6.4520548
Median Absolute Deviation (MAD)	2
Skewness	-0.082005805
Sum	471
Variance	4.445586
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
5	14	18.9%
6	13	17.6%
8	12	16.2%
9	8	10.8%
7	8	10.8%
10	6	8.1%
4	5	6.8%
3	5	6.8%
2	2	2.7%
(Missing)	1	1.4%

Value	Count	Frequency (%)
2	2	2.7%
3	5	6.8%
4	5	6.8%
5	14	18.9%
6	13	17.6%
7	8	10.8%
8	12	16.2%
9	8	10.8%
10	6	8.1%

Value	Count	Frequency (%)
10	6	8.1%
9	8	10.8%
8	12	16.2%
7	8	10.8%
6	13	17.6%
5	14	18.9%
4	5	6.8%
3	5	6.8%
2	2	2.7%

second_ings_score
Real number (ℝ)

High correlation Missing

Distinct	51
Distinct (%)	70.8%
Missing	2
Missing (%)	2.7%
Infinite	0
Infinite (%)	0.0%
Mean	174.01389

Minimum	7
Maximum	247
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	724.0 B

Quantile statistics

Minimum	7
5-th percentile	106.55
Q1	158
median	177
Q3	201.25
95-th percentile	230.9
Maximum	247
Range	240
Interquartile range (IQR)	43.25

Descriptive statistics

Standard deviation	38.805217
Coefficient of variation (CV)	0.22300069
Kurtosis	3.8502523
Mean	174.01389
Median Absolute Deviation (MAD)	22
Skewness	-1.2679678
Sum	12529
Variance	1505.8449
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
177	3	4.1%
159	3	4.1%
211	2	2.7%
158	2	2.7%
121	2	2.7%
153	2	2.7%
146	2	2.7%
193	2	2.7%
155	2	2.7%
209	2	2.7%
Other values (41)	50	67.6%

Value	Count	Frequency (%)
7	1	1.4%
95	1	1.4%
98	1	1.4%
106	1	1.4%
107	1	1.4%
117	1	1.4%
120	1	1.4%
121	2	2.7%
146	2	2.7%
147	2	2.7%

Value	Count	Frequency (%)
247	1	1.4%
242	1	1.4%
234	1	1.4%
232	1	1.4%
230	1	1.4%
212	1	1.4%
211	2	2.7%
209	2	2.7%
208	2	2.7%
207	1	1.4%

second_ings_wkts
Real number (ℝ)

High correlation Missing Zeros

Distinct	11
Distinct (%)	15.3%
Missing	2
Missing (%)	2.7%
Infinite	0
Infinite (%)	0.0%
Mean	5.5138889

Minimum	0
Maximum	10
Zeros	2
Zeros (%)	2.7%
Negative	0
Negative (%)	0.0%
Memory size	724.0 B

Quantile statistics

Minimum	0
5-th percentile	1.55
Q1	3
median	5
Q3	8
95-th percentile	10
Maximum	10
Range	10
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	2.8826487
Coefficient of variation (CV)	0.52279775
Kurtosis	-1.0251697
Mean	5.5138889
Median Absolute Deviation (MAD)	2
Skewness	0.11228863
Sum	397
Variance	8.3096635
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
5	11	14.9%
10	10	13.5%
2	9	12.2%
6	8	10.8%
4	8	10.8%
3	7	9.5%
9	6	8.1%
7	5	6.8%
8	4	5.4%
1	2	2.7%

Value	Count	Frequency (%)
0	2	2.7%
1	2	2.7%
2	9	12.2%
3	7	9.5%
4	8	10.8%
5	11	14.9%
6	8	10.8%
7	5	6.8%
8	4	5.4%
9	6	8.1%

Value	Count	Frequency (%)
10	10	13.5%
9	6	8.1%
8	4	5.4%
7	5	6.8%
6	8	10.8%
5	11	14.9%
4	8	10.8%
3	7	9.5%
2	9	12.2%
1	2	2.7%

match_result
Categorical

High correlation Imbalance

Distinct	2
Distinct (%)	2.7%
Missing	0
Missing (%)	0.0%
Memory size	4.9 KiB

completed	71
tied	3

Length

Max length	9
Median length	9
Mean length	8.7972973
Min length	4

Characters and Unicode

Total characters	651
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	completed
2nd row	completed
3rd row	completed
4th row	completed
5th row	completed

Common Values

Value	Count	Frequency (%)
completed	71	95.9%
tied	3	4.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
completed	71	95.9%
tied	3	4.1%

Most occurring characters

Value	Count	Frequency (%)
e	145	22.3%
d	74	11.4%
t	74	11.4%
c	71	10.9%
o	71	10.9%
l	71	10.9%
p	71	10.9%
m	71	10.9%
i	3	0.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	651	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
e	145	22.3%
d	74	11.4%
t	74	11.4%
c	71	10.9%
o	71	10.9%
l	71	10.9%
p	71	10.9%
m	71	10.9%
i	3	0.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	651	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
e	145	22.3%
d	74	11.4%
t	74	11.4%
c	71	10.9%
o	71	10.9%
l	71	10.9%
p	71	10.9%
m	71	10.9%
i	3	0.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	651	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
e	145	22.3%
d	74	11.4%
t	74	11.4%
c	71	10.9%
o	71	10.9%
l	71	10.9%
p	71	10.9%
m	71	10.9%
i	3	0.5%

match_winner
Categorical

High correlation Missing

Distinct	10
Distinct (%)	14.1%
Missing	3
Missing (%)	4.1%
Memory size	4.5 KiB

PBKS	11
RCB	10
GT	9
MI	8
DC	8
Other values (5)	25

Length

Max length	4
Median length	3
Mean length	2.7464789
Min length	2

Characters and Unicode

Total characters	195
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	RCB
2nd row	SRH
3rd row	CSK
4th row	DC
5th row	PBKS

Common Values

Value	Count	Frequency (%)
PBKS	11	14.9%
RCB	10	13.5%
GT	9	12.2%
MI	8	10.8%
DC	8	10.8%
LSG	6	8.1%
SRH	6	8.1%
KKR	5	6.8%
CSK	4	5.4%
RR	4	5.4%
(Missing)	3	4.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
pbks	11	15.5%
rcb	10	14.1%
gt	9	12.7%
mi	8	11.3%
dc	8	11.3%
lsg	6	8.5%
srh	6	8.5%
kkr	5	7.0%
csk	4	5.6%
rr	4	5.6%

Most occurring characters

Value	Count	Frequency (%)
R	29	14.9%
S	27	13.8%
K	25	12.8%
C	22	11.3%
B	21	10.8%
G	15	7.7%
P	11	5.6%
T	9	4.6%
M	8	4.1%
I	8	4.1%
Other values (3)	20	10.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	195	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
R	29	14.9%
S	27	13.8%
K	25	12.8%
C	22	11.3%
B	21	10.8%
G	15	7.7%
P	11	5.6%
T	9	4.6%
M	8	4.1%
I	8	4.1%
Other values (3)	20	10.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	195	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
R	29	14.9%
S	27	13.8%
K	25	12.8%
C	22	11.3%
B	21	10.8%
G	15	7.7%
P	11	5.6%
T	9	4.6%
M	8	4.1%
I	8	4.1%
Other values (3)	20	10.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	195	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
R	29	14.9%
S	27	13.8%
K	25	12.8%
C	22	11.3%
B	21	10.8%
G	15	7.7%
P	11	5.6%
T	9	4.6%
M	8	4.1%
I	8	4.1%
Other values (3)	20	10.3%

wb_runs
Text

Missing

Distinct	28
Distinct (%)	82.4%
Missing	40
Missing (%)	54.1%
Memory size	3.3 KiB

Length

Max length	10
Median length	2
Mean length	2.1176471
Min length	1

Characters and Unicode

Total characters	72
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	23 ?
Unique (%)	67.6%

Sample

1st row	44
2nd row	11
3rd row	50
4th row	36
5th row	6

Value	Count	Frequency (%)
12	3	8.6%
11	2	5.7%
6	2	5.7%
50	2	5.7%
2	2	5.7%
36	1	2.9%
80	1	2.9%
44	1	2.9%
4	1	2.9%
18	1	2.9%
Other values (19)	19	54.3%

Most occurring characters

Value	Count	Frequency (%)
1	15	20.8%
2	8	11.1%
0	8	11.1%
3	7	9.7%
5	6	8.3%
4	6	8.3%
8	5	6.9%
6	4	5.6%
r	2	2.8%
e	2	2.8%
Other values (8)	9	12.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	72	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
1	15	20.8%
2	8	11.1%
0	8	11.1%
3	7	9.7%
5	6	8.3%
4	6	8.3%
8	5	6.9%
6	4	5.6%
r	2	2.8%
e	2	2.8%
Other values (8)	9	12.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	72	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
1	15	20.8%
2	8	11.1%
0	8	11.1%
3	7	9.7%
5	6	8.3%
4	6	8.3%
8	5	6.9%
6	4	5.6%
r	2	2.8%
e	2	2.8%
Other values (8)	9	12.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	72	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
1	15	20.8%
2	8	11.1%
0	8	11.1%
3	7	9.7%
5	6	8.3%
4	6	8.3%
8	5	6.9%
6	4	5.6%
r	2	2.8%
e	2	2.8%
Other values (8)	9	12.5%

wb_wickets
Categorical

High correlation Missing

Distinct	11
Distinct (%)	28.9%
Missing	36
Missing (%)	48.6%
Memory size	4.5 KiB

8	9
6	7
7	7
5	5
4	3
Other values (6)	7

Length

Max length	10
Median length	1
Mean length	1.2631579
Min length	1

Characters and Unicode

Total characters	48
Distinct characters	18
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	13.2%

Sample

1st row	7
2nd row	4
3rd row	1
4th row	8
5th row	5

Common Values

Value	Count	Frequency (%)
8	9	12.2%
6	7	9.5%
7	7	9.5%
5	5	6.8%
4	3	4.1%
9	2	2.7%
1	1	1.4%
super over	1	1.4%
3	1	1.4%
2	1	1.4%
(Missing)	36	48.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
8	9	23.1%
6	7	17.9%
7	7	17.9%
5	5	12.8%
4	3	7.7%
9	2	5.1%
1	1	2.6%
super	1	2.6%
over	1	2.6%
3	1	2.6%
Other values (2)	2	5.1%

Most occurring characters

Value	Count	Frequency (%)
8	9	18.8%
6	7	14.6%
7	7	14.6%
5	5	10.4%
4	3	6.2%
9	2	4.2%
1	2	4.2%
e	2	4.2%
r	2	4.2%
s	1	2.1%
Other values (8)	8	16.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	48	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
8	9	18.8%
6	7	14.6%
7	7	14.6%
5	5	10.4%
4	3	6.2%
9	2	4.2%
1	2	4.2%
e	2	4.2%
r	2	4.2%
s	1	2.1%
Other values (8)	8	16.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	48	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
8	9	18.8%
6	7	14.6%
7	7	14.6%
5	5	10.4%
4	3	6.2%
9	2	4.2%
1	2	4.2%
e	2	4.2%
r	2	4.2%
s	1	2.1%
Other values (8)	8	16.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	48	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
8	9	18.8%
6	7	14.6%
7	7	14.6%
5	5	10.4%
4	3	6.2%
9	2	4.2%
1	2	4.2%
e	2	4.2%
r	2	4.2%
s	1	2.1%
Other values (8)	8	16.7%

balls_left
Real number (ℝ)

High correlation Missing Zeros

Distinct	26
Distinct (%)	36.1%
Missing	2
Missing (%)	2.7%
Infinite	0
Infinite (%)	0.0%
Mean	10.819444

Minimum	0
Maximum	114
Zeros	26
Zeros (%)	35.1%
Negative	0
Negative (%)	0.0%
Memory size	724.0 B

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	5.5
Q3	13.5
95-th percentile	35.3
Maximum	114
Range	114
Interquartile range (IQR)	13.5

Descriptive statistics

Standard deviation	17.674942
Coefficient of variation (CV)	1.6336275
Kurtosis	16.724088
Mean	10.819444
Median Absolute Deviation (MAD)	5.5
Skewness	3.5436021
Sum	779
Variance	312.40356
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=26)

Value	Count	Frequency (%)
0	26	35.1%
3	4	5.4%
9	4	5.4%
6	3	4.1%
8	3	4.1%
13	3	4.1%
4	2	2.7%
20	2	2.7%
22	2	2.7%
23	2	2.7%
Other values (16)	21	28.4%

Value	Count	Frequency (%)
0	26	35.1%
1	1	1.4%
2	2	2.7%
3	4	5.4%
4	2	2.7%
5	1	1.4%
6	3	4.1%
7	1	1.4%
8	3	4.1%
9	4	5.4%

Value	Count	Frequency (%)
114	1	1.4%
60	1	1.4%
59	1	1.4%
43	1	1.4%
29	1	1.4%
26	2	2.7%
25	1	1.4%
24	1	1.4%
23	2	2.7%
22	2	2.7%

player_of_the_match
Text

Missing

Distinct	53
Distinct (%)	74.6%
Missing	3
Missing (%)	4.1%
Memory size	5.1 KiB

Length

Max length	19
Median length	16
Mean length	12.774648
Min length	8

Characters and Unicode

Total characters	907
Distinct characters	45
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	37 ?
Unique (%)	52.1%

Sample

1st row	Krunal Pandya
2nd row	Ishan Kishan
3rd row	Noor Ahmad
4th row	Ashutosh Sharma
5th row	Shreyas Iyer

Value	Count	Frequency (%)
sharma	8	5.6%
krunal	3	2.1%
pandya	3	2.1%
iyer	3	2.1%
shreyas	3	2.1%
mitchell	3	2.1%
singh	3	2.1%
kishan	2	1.4%
prasidh	2	1.4%
noor	2	1.4%
Other values (87)	111	77.6%

Most occurring characters

Value	Count	Frequency (%)
a	119	13.1%
h	75	8.3%
	72	7.9%
r	71	7.8%
i	58	6.4%
n	44	4.9%
s	43	4.7%
e	40	4.4%
l	39	4.3%
S	34	3.7%
Other values (35)	312	34.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	907	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	119	13.1%
h	75	8.3%
	72	7.9%
r	71	7.8%
i	58	6.4%
n	44	4.9%
s	43	4.7%
e	40	4.4%
l	39	4.3%
S	34	3.7%
Other values (35)	312	34.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	907	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	119	13.1%
h	75	8.3%
	72	7.9%
r	71	7.8%
i	58	6.4%
n	44	4.9%
s	43	4.7%
e	40	4.4%
l	39	4.3%
S	34	3.7%
Other values (35)	312	34.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	907	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	119	13.1%
h	75	8.3%
	72	7.9%
r	71	7.8%
i	58	6.4%
n	44	4.9%
s	43	4.7%
e	40	4.4%
l	39	4.3%
S	34	3.7%
Other values (35)	312	34.4%

top_scorer
Text

Missing

Distinct	41
Distinct (%)	57.7%
Missing	3
Missing (%)	4.1%
Memory size	5.1 KiB

Length

Max length	20
Median length	16
Mean length	13.056338
Min length	8

Characters and Unicode

Total characters	927
Distinct characters	45
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	21 ?
Unique (%)	29.6%

Sample

1st row	Virat Kohli
2nd row	Ishan Kishan
3rd row	Rachin Ravindra
4th row	Nicholas Pooran
5th row	Shreyas Iyer

Value	Count	Frequency (%)
virat	4	2.8%
kohli	4	2.8%
nicholas	4	2.8%
pooran	4	2.8%
sharma	4	2.8%
kishan	3	2.1%
sai	3	2.1%
sudarshan	3	2.1%
ishan	3	2.1%
gill	3	2.1%
Other values (71)	109	75.7%

Most occurring characters

Value	Count	Frequency (%)
a	127	13.7%
i	77	8.3%
	73	7.9%
h	73	7.9%
s	56	6.0%
n	55	5.9%
r	54	5.8%
l	42	4.5%
e	34	3.7%
S	27	2.9%
Other values (35)	309	33.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	927	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	127	13.7%
i	77	8.3%
	73	7.9%
h	73	7.9%
s	56	6.0%
n	55	5.9%
r	54	5.8%
l	42	4.5%
e	34	3.7%
S	27	2.9%
Other values (35)	309	33.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	927	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	127	13.7%
i	77	8.3%
	73	7.9%
h	73	7.9%
s	56	6.0%
n	55	5.9%
r	54	5.8%
l	42	4.5%
e	34	3.7%
S	27	2.9%
Other values (35)	309	33.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	927	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	127	13.7%
i	77	8.3%
	73	7.9%
h	73	7.9%
s	56	6.0%
n	55	5.9%
r	54	5.8%
l	42	4.5%
e	34	3.7%
S	27	2.9%
Other values (35)	309	33.3%

highscore
Real number (ℝ)

High correlation Missing

Distinct	44
Distinct (%)	62.0%
Missing	3
Missing (%)	4.1%
Infinite	0
Infinite (%)	0.0%
Mean	74.549296

Minimum	37
Maximum	141
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	724.0 B

Quantile statistics

Minimum	37
5-th percentile	47
Q1	61
median	73
Q3	88.5
95-th percentile	107
Maximum	141
Range	104
Interquartile range (IQR)	27.5

Descriptive statistics

Standard deviation	20.088226
Coefficient of variation (CV)	0.26946232
Kurtosis	0.65751389
Mean	74.549296
Median Absolute Deviation (MAD)	14
Skewness	0.7245618
Sum	5293
Variance	403.53682
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=44)

Value	Count	Frequency (%)
73	5	6.8%
61	4	5.4%
70	3	4.1%
67	3	4.1%
97	3	4.1%
57	3	4.1%
63	2	2.7%
51	2	2.7%
74	2	2.7%
81	2	2.7%
Other values (34)	42	56.8%
(Missing)	3	4.1%

Value	Count	Frequency (%)
37	1	1.4%
40	1	1.4%
44	2	2.7%
50	1	1.4%
51	2	2.7%
52	1	1.4%
53	1	1.4%
56	1	1.4%
57	3	4.1%
58	2	2.7%

Value	Count	Frequency (%)
141	1	1.4%
118	1	1.4%
117	1	1.4%
108	1	1.4%
106	1	1.4%
105	1	1.4%
103	1	1.4%
101	1	1.4%
97	3	4.1%
95	1	1.4%

best_bowling
Text

Missing

Distinct	42
Distinct (%)	59.2%
Missing	3
Missing (%)	4.1%
Memory size	5.1 KiB

Length

Max length	18
Median length	16
Mean length	13.56338
Min length	10

Characters and Unicode

Total characters	963
Distinct characters	46
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	24 ?
Unique (%)	33.8%

Sample

1st row	Krunal Pandya
2nd row	Tushar Deshpande
3rd row	Noor Ahmad
4th row	Mitchell Starc
5th row	Sai Kishore

Value	Count	Frequency (%)
prasidh	5	3.5%
krishna	5	3.5%
pandya	5	3.5%
krunal	4	2.8%
arshdeep	4	2.8%
singh	4	2.8%
josh	3	2.1%
hazlewood	3	2.1%
varun	3	2.1%
chakravarthy	3	2.1%
Other values (68)	103	72.5%

Most occurring characters

Value	Count	Frequency (%)
a	132	13.7%
r	81	8.4%
h	77	8.0%
	71	7.4%
n	52	5.4%
e	50	5.2%
i	48	5.0%
s	43	4.5%
d	38	3.9%
u	35	3.6%
Other values (36)	336	34.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	963	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	132	13.7%
r	81	8.4%
h	77	8.0%
	71	7.4%
n	52	5.4%
e	50	5.2%
i	48	5.0%
s	43	4.5%
d	38	3.9%
u	35	3.6%
Other values (36)	336	34.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	963	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	132	13.7%
r	81	8.4%
h	77	8.0%
	71	7.4%
n	52	5.4%
e	50	5.2%
i	48	5.0%
s	43	4.5%
d	38	3.9%
u	35	3.6%
Other values (36)	336	34.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	963	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	132	13.7%
r	81	8.4%
h	77	8.0%
	71	7.4%
n	52	5.4%
e	50	5.2%
i	48	5.0%
s	43	4.5%
d	38	3.9%
u	35	3.6%
Other values (36)	336	34.9%

best_bowling_figure
Text

Missing

Distinct	54
Distinct (%)	76.1%
Missing	3
Missing (%)	4.1%
Memory size	4.5 KiB

Length

Max length	5
Median length	5
Mean length	4.9859155
Min length	4

Characters and Unicode

Total characters	354
Distinct characters	11
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	40 ?
Unique (%)	56.3%

Sample

1st row	3--29
2nd row	3--44
3rd row	4--18
4th row	3--42
5th row	3--30

Value	Count	Frequency (%)
2--25	4	5.6%
3--29	3	4.2%
2--18	2	2.8%
3--22	2	2.8%
3--21	2	2.8%
2--17	2	2.8%
3--24	2	2.8%
2--28	2	2.8%
3--33	2	2.8%
4--33	2	2.8%
Other values (44)	48	67.6%

Most occurring characters

Value	Count	Frequency (%)
-	142	40.1%
3	58	16.4%
2	55	15.5%
4	33	9.3%
1	21	5.9%
5	13	3.7%
8	8	2.3%
7	8	2.3%
9	6	1.7%
6	6	1.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	354	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
-	142	40.1%
3	58	16.4%
2	55	15.5%
4	33	9.3%
1	21	5.9%
5	13	3.7%
8	8	2.3%
7	8	2.3%
9	6	1.7%
6	6	1.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	354	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
-	142	40.1%
3	58	16.4%
2	55	15.5%
4	33	9.3%
1	21	5.9%
5	13	3.7%
8	8	2.3%
7	8	2.3%
9	6	1.7%
6	6	1.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	354	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
-	142	40.1%
3	58	16.4%
2	55	15.5%
4	33	9.3%
1	21	5.9%
5	13	3.7%
8	8	2.3%
7	8	2.3%
9	6	1.7%
6	6	1.7%

Interactions

Correlations

	balls_left	first_ings_score	first_ings_wkts	highscore	match_id	match_result	match_winner	second_ings_score	second_ings_wkts	stage	team1	team2	toss_decision	toss_winner	venue	wb_wickets
balls_left	1.000	-0.530	0.266	-0.236	-0.061	0.971	0.075	-0.450	-0.509	0.108	0.059	0.036	0.203	0.000	0.000	0.000
first_ings_score	-0.530	1.000	-0.596	0.542	0.202	0.385	0.205	0.661	0.453	0.000	0.181	0.117	0.000	0.000	0.182	0.000
first_ings_wkts	0.266	-0.596	1.000	-0.434	-0.276	0.168	0.184	-0.317	-0.213	0.000	0.179	0.122	0.226	0.140	0.197	0.202
highscore	-0.236	0.542	-0.434	1.000	0.035	1.000	0.000	0.579	-0.060	0.069	0.000	0.000	0.230	0.000	0.000	0.000
match_id	-0.061	0.202	-0.276	0.035	1.000	0.289	0.000	0.142	0.132	0.340	0.000	0.000	0.184	0.000	0.000	0.178
match_result	0.971	0.385	0.168	1.000	0.289	1.000	1.000	0.956	0.338	0.000	0.000	0.000	0.000	0.000	0.000	1.000
match_winner	0.075	0.205	0.184	0.000	0.000	1.000	1.000	0.122	0.000	0.000	0.284	0.476	0.130	0.496	0.212	0.000
second_ings_score	-0.450	0.661	-0.317	0.579	0.142	0.956	0.122	1.000	-0.005	0.000	0.000	0.000	0.181	0.000	0.000	0.000
second_ings_wkts	-0.509	0.453	-0.213	-0.060	0.132	0.338	0.000	-0.005	1.000	0.048	0.099	0.149	0.000	0.160	0.104	0.965
stage	0.108	0.000	0.000	0.069	0.340	0.000	0.000	0.000	0.048	1.000	0.104	0.104	0.000	0.000	0.013	0.000
team1	0.059	0.181	0.179	0.000	0.000	0.000	0.284	0.000	0.099	0.104	1.000	0.000	0.185	0.224	0.864	0.000
team2	0.036	0.117	0.122	0.000	0.000	0.000	0.476	0.000	0.149	0.104	0.000	1.000	0.034	0.565	0.000	0.216
toss_decision	0.203	0.000	0.226	0.230	0.184	0.000	0.130	0.181	0.000	0.000	0.185	0.034	1.000	0.149	0.194	0.317
toss_winner	0.000	0.000	0.140	0.000	0.000	0.000	0.496	0.000	0.160	0.000	0.224	0.565	0.149	1.000	0.224	0.000
venue	0.000	0.182	0.197	0.000	0.000	0.000	0.212	0.000	0.104	0.013	0.864	0.000	0.194	0.224	1.000	0.072
wb_wickets	0.000	0.000	0.202	0.000	0.178	1.000	0.000	0.000	0.965	0.000	0.000	0.216	0.317	0.000	0.072	1.000

Missing values

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

	match_id	date	venue	team1	team2	stage	toss_winner	toss_decision	first_ings_score	first_ings_wkts	second_ings_score	second_ings_wkts	match_result	match_winner	wb_runs	wb_wickets	balls_left	player_of_the_match	top_scorer	highscore	best_bowling	best_bowling_figure
0	1	March 22,2025	Eden Gardens, Kolkata	KKR	RCB	League	RCB	Bowl	174.0	8.0	177.0	3.0	completed	RCB	NaN	7	22.0	Krunal Pandya	Virat Kohli	59.0	Krunal Pandya	3--29
1	2	March 23,2025	Rajiv Gandhi International Stadium, Hyderabad	SRH	RR	League	RR	Bowl	286.0	6.0	242.0	6.0	completed	SRH	44	NaN	0.0	Ishan Kishan	Ishan Kishan	106.0	Tushar Deshpande	3--44
2	3	March 23,2025	MA Chidambaram Stadium, Chennai	CSK	MI	League	CSK	Bowl	155.0	9.0	158.0	6.0	completed	CSK	NaN	4	5.0	Noor Ahmad	Rachin Ravindra	65.0	Noor Ahmad	4--18
3	4	March 24,2025	ACA-VDCA Cricket Stadium, Vishakhapatnam	DC	LSG	League	DC	Bowl	209.0	8.0	211.0	9.0	completed	DC	NaN	1	3.0	Ashutosh Sharma	Nicholas Pooran	75.0	Mitchell Starc	3--42
4	5	March 25,2025	Narendra Modi Stadium, Ahmedabad	GT	PBKS	League	GT	Bowl	243.0	5.0	232.0	5.0	completed	PBKS	11	NaN	0.0	Shreyas Iyer	Shreyas Iyer	97.0	Sai Kishore	3--30
5	6	March 26,2025	Barsapara Stadium, Guwahati	RR	KKR	League	KKR	Bowl	151.0	9.0	153.0	2.0	completed	KKR	NaN	8	15.0	Quinton de Kock	Quinton de Kock	97.0	Varun Chakravarthy	2--17
6	7	March 27,2025	Rajiv Gandhi International Stadium, Hyderabad	SRH	LSG	League	LSG	Bowl	190.0	9.0	193.0	5.0	completed	LSG	NaN	5	23.0	Shardul Thakur	Nicholas Pooran	70.0	Shardul Thakur	4--34
7	8	March 28,2025	MA Chidambaram Stadium, Chennai	CSK	RCB	League	CSK	Bowl	196.0	7.0	146.0	8.0	completed	RCB	50	NaN	0.0	Rajat Patidar	Rajat Patidar	51.0	Josh Hazlewood	3--21
8	9	March 29,2025	Narendra Modi Stadium, Ahmedabad	GT	MI	League	MI	Bowl	196.0	8.0	160.0	6.0	completed	GT	36	NaN	0.0	Prasidh Krishna	Sai Sudarshan	63.0	Prasidh Krishna	2--18
9	10	March 30,2025	ACA-VDCA Cricket Stadium, Vishakhapatnam	DC	SRH	League	SRH	Bat	163.0	10.0	166.0	3.0	completed	DC	NaN	7	24.0	Mitchell Starc	Aniket Verma	74.0	Mitchell Starc	5--35

	match_id	date	venue	team1	team2	stage	toss_winner	toss_decision	first_ings_score	first_ings_wkts	second_ings_score	second_ings_wkts	match_result	match_winner	wb_runs	wb_wickets	balls_left	player_of_the_match	top_scorer	highscore	best_bowling	best_bowling_figure
64	65	May 23,2025	Ekana Cricket Stadium, Lucknow	RCB	SRH	League	RCB	Bowl	231.0	6.0	189.0	10.0	completed	SRH	42	NaN	1.0	Ishan Kishan	Ishan Kishan	94.0	Pat Cummins	3--28
65	66	May 24,2025	Sawai Mansingh Stadium, Jaipur	PBKS	DC	League	DC	Bowl	206.0	8.0	208.0	4.0	completed	DC	NaN	6	3.0	Sameer Rizvi	Sameer Rizvi	58.0	Mustafizur Rahman	3--33
66	67	May 25,2025	Narendra Modi Stadium, Ahmedabad	GT	CSK	League	CSK	Bat	230.0	5.0	147.0	10.0	completed	CSK	83	NaN	9.0	Dewald Brevis	Dewald Brevis	57.0	Noor Ahmad	3--21
67	68	May 25,2025	Arun Jaitley Stadium, Delhi	KKR	SRH	League	SRH	Bat	278.0	3.0	168.0	10.0	completed	SRH	110	NaN	8.0	Heinrich Klassen	Heinrich Klassen	105.0	Jaydev Unadkat	3--24
68	69	May 26,2025	Sawai Mansingh Stadium, Jaipur	PBKS	MI	League	PBKS	Bowl	184.0	7.0	187.0	3.0	completed	PBKS	NaN	7	9.0	Josh Inglis	Josh Inglis	73.0	Arshdeep Singh	2--28
69	70	May 27,2025	Ekana Cricket Stadium, Lucknow	LSG	RCB	League	RCB	Bowl	227.0	3.0	230.0	4.0	completed	RCB	NaN	6	8.0	Jitesh Sharma	Rishabh Pant	118.0	Will O'Rourke	2--74
70	71	May 29,2025	New PCA Cricket Stadium, Mullanpur	PBKS	RCB	Playoffs	RCB	Bowl	101.0	10.0	106.0	2.0	completed	RCB	NaN	8	60.0	Suyash Sharma	Phil Salt	56.0	Suyash Sharma	3--17
71	72	May 30,2025	New PCA Cricket Stadium, Mullanpur	GT	MI	Playoffs	MI	Bat	228.0	5.0	208.0	6.0	completed	MI	20	NaN	0.0	Rohit Sharma	Rohit Sharma	81.0	Sai Kishore	2--42
72	73	June 1,2025	Narendra Modi Stadium, Ahmedabad	PBKS	MI	Playoffs	PBKS	Bowl	203.0	6.0	207.0	5.0	completed	PBKS	NaN	5	6.0	Shreyas Iyer	Shreyas Iyer	87.0	Azmatullah Omarzai	2--43
73	74	June 3,2025	Narendra Modi Stadium, Ahmedabad	RCB	PBKS	Final	PBKS	Bowl	190.0	9.0	184.0	7.0	completed	RCB	6	NaN	0.0	Krunal Pandya	Shashank Singh	61.0	Arshdeep Singh	3--40

Overview

Variables

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters